Evidence map›Paper›PMID 36225823›Full record

ArticleEcology and evolution2022

Intra-annual growing season climate variability drives the community intra-annual stability of a temperate grassland by altering intra-annual species asynchrony and richness in Inner Mongolia, China.

Ze Zhang, Tiejun Bao, Yann Hautier, Jie Yang, Zhongling Liu, Hua Qing

Abstract read
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Article in Ecology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ze ZhangMinistry of Education Key Laboratory of Ecology and Resource Use of the Mongolian Plateau Inner Mongolia University Hohhot China.ORCID https://orcid.org/0000-0003-1839-9964
Tiejun BaoMinistry of Education Key Laboratory of Ecology and Resource Use of the Mongolian Plateau Inner Mongolia University Hohhot China.
Yann HautierEcology and Biodiversity Group, Department of Biology Utrecht University Utrecht Netherlands.
Jie YangMinistry of Education Key Laboratory of Ecology and Resource Use of the Mongolian Plateau Inner Mongolia University Hohhot China.
Zhongling LiuMinistry of Education Key Laboratory of Ecology and Resource Use of the Mongolian Plateau Inner Mongolia University Hohhot China.
Hua QingMinistry of Education Key Laboratory of Ecology and Resource Use of the Mongolian Plateau Inner Mongolia University Hohhot China.ORCID https://orcid.org/0000-0002-7429-2451

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the factors that regulate the functioning of our ecosystems in response to environmental changes can help to maintain the stable provisioning of ecosystem services to mankind. This is especially relevant given the increased variability of environmental conditions due to human activities. In particular, maintaining a stable production and plant biomass during the growing season (intra-annual stability) despite pervasive and directional changes in temperature and precipitation through time can help to secure food supply to wild animals, livestock, and humans. Here, we conducted a 29-year field observational study in a temperate grassland to explore how the intra-annual stability of primary productivity is influenced by biotic and abiotic variables through time. We found that intra-annual precipitation variability in the growing season indirectly influenced the community intra-annual biomass stability by its negative effect on intra-annual species asynchrony. While the intra-annual temperature variability in the growing season indirectly altered community intra-annual biomass stability through affecting the intra-annual species richness. At the same time, although the intra-annual biomass stability of the dominant species and the dominant functional group were insensitive to climate variability, they also promoted the stable community biomass to a certain extent. Our results indicate that ongoing intra-annual climate variability affects community intra-annual biomass stability in the temperate grassland, which has important theoretical significance for us to take active measures to deal with climate change.

Indexed as

climate variabilitydominant species intra‐annual stabilityfunctional group intra‐annual stabilityintra‐annual species asynchronyintra‐annual species richnesslong‐term observation

Identifiers

PMID36225823
PMCPMC9532246

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.